def T2m_all_type(initTime=None,
fhour=24,
day_back=0,
model='中央气象台中短期指导',
Var_plot='Tmn_2m',
map_ratio=19 / 9,
zoom_ratio=20,
cntr_pnt=[102, 34],
data_source='MICAPS',
south_China_sea=True,
area='全国',
city=False,
output_dir=None,
Global=False):
# prepare data
if (data_source == 'MICAPS'):
try:
data_dir = [
utl.Cassandra_dir(data_type='surface',
data_source=model,
var_name=Var_plot)
]
except KeyError:
raise ValueError('Can not find all directories needed')
if (initTime != None):
filename = utl.model_filename(initTime, fhour)
else:
filename = utl.filename_day_back_model(day_back=day_back,
fhour=fhour)
T_2m = MICAPS_IO.get_model_grid(data_dir[0], filename=filename)
if T_2m is None:
return
if (data_source == 'CIMISS'):
# get filename
if (initTime != None):
filename = utl.model_filename(initTime, fhour, UTC=True)
else:
filename = utl.filename_day_back_model(day_back=day_back,
fhour=fhour,
UTC=True)
try:
# retrieve data from CMISS server
T_2m = CMISS_IO.cimiss_model_by_time(
'20' + filename[0:8],
valid_time=fhour,
data_code=utl.CMISS_data_code(data_source=model,
var_name='TEF2'),
levattrs={
'long_name': 'Mean_sea_level',
'units': 'm',
'_CoordinateAxisType': '-'
},
fcst_level=0,
fcst_ele="TEF2",
units='K')
if T_2m is None:
return
T_2m['data'].values = T_2m['data'].values - 273.15
except KeyError:
raise ValueError('Can not find all data needed')
# set map extent
if (area != '全国'):
south_China_sea = False
if (area != None):
cntr_pnt, zoom_ratio = utl.get_map_area(area_name=area)
map_extent = [0, 0, 0, 0]
map_extent[0] = cntr_pnt[0] - zoom_ratio * 1 * map_ratio
map_extent[1] = cntr_pnt[0] + zoom_ratio * 1 * map_ratio
map_extent[2] = cntr_pnt[1] - zoom_ratio * 1
map_extent[3] = cntr_pnt[1] + zoom_ratio * 1
delt_x = (map_extent[1] - map_extent[0]) * 0.2
delt_y = (map_extent[3] - map_extent[2]) * 0.1
#+ to solve the problem of labels on all the contours
mask1 = (T_2m['lon'] > map_extent[0] - delt_x) & (
T_2m['lon'] < map_extent[1] + delt_x) & (
T_2m['lat'] > map_extent[2] - delt_y) & (T_2m['lat'] <
map_extent[3] + delt_y)
T_2m = T_2m.where(mask1, drop=True)
titles = {
'Tmn_2m': '过去24小时2米最低温度',
'Tmx_2m': '过去24小时2米最高温度',
'T2m': '2米温度'
}
#- to solve the problem of labels on all the contours
T_2m.attrs['model'] = model
T_2m.attrs['title'] = titles[Var_plot]
elements_graphics.draw_T_2m(T_2m=T_2m,
map_extent=map_extent,
regrid_shape=20,
city=city,
south_China_sea=south_China_sea,
output_dir=output_dir,
Global=Global)
def T2m_all_type(initTime=None,
fhour=24,
day_back=0,
model='中央台指导',
Var_plot='Tmn_2m',
map_ratio=19 / 9,
zoom_ratio=20,
cntr_pnt=[102, 34],
south_China_sea=True,
area='全国',
city=False,
output_dir=None,
Global=False):
if (area != '全国'):
south_China_sea = False
# micaps data directory
try:
data_dir = [
utl.Cassandra_dir(data_type='surface',
data_source=model,
var_name=Var_plot)
]
except KeyError:
raise ValueError('Can not find all directories needed')
# get filename
if (initTime != None):
filename = utl.model_filename(initTime, fhour)
else:
filename = utl.filename_day_back_model(day_back=day_back, fhour=fhour)
# retrieve data from micaps server
T_2m = get_model_grid(data_dir[0], filename=filename)
if T_2m is None:
return
init_time = T_2m.coords['forecast_reference_time'].values
# prepare data
if (area != None):
cntr_pnt, zoom_ratio = utl.get_map_area(area_name=area)
map_extent = [0, 0, 0, 0]
map_extent[0] = cntr_pnt[0] - zoom_ratio * 1 * map_ratio
map_extent[1] = cntr_pnt[0] + zoom_ratio * 1 * map_ratio
map_extent[2] = cntr_pnt[1] - zoom_ratio * 1
map_extent[3] = cntr_pnt[1] + zoom_ratio * 1
delt_x = (map_extent[1] - map_extent[0]) * 0.2
delt_y = (map_extent[3] - map_extent[2]) * 0.1
#+ to solve the problem of labels on all the contours
idx_x1 = np.where((T_2m.coords['lon'].values > map_extent[0] - delt_x)
& (T_2m.coords['lon'].values < map_extent[1] + delt_x))
idx_y1 = np.where((T_2m.coords['lat'].values > map_extent[2] - delt_y)
& (T_2m.coords['lat'].values < map_extent[3] + delt_y))
titles = {
'Tmn_2m': '过去24小时2米最低温度',
'Tmx_2m': '过去24小时2米最高温度',
'T2m': '2米温度'
}
#- to solve the problem of labels on all the contours
T_2m = {
'lon':
T_2m.coords['lon'].values[idx_x1],
'lat':
T_2m.coords['lat'].values[idx_y1],
'data':
T_2m['data'].values[0, 0, idx_y1[0][0]:(idx_y1[0][-1] + 1),
idx_x1[0][0]:(idx_x1[0][-1] + 1)],
'model':
model,
'fhour':
fhour,
'title':
titles[Var_plot],
'init_time':
init_time
}
elements_graphics.draw_T_2m(T_2m=T_2m,
map_extent=map_extent,
regrid_shape=20,
city=city,
south_China_sea=south_China_sea,
output_dir=output_dir,
Global=Global)
def T2m_mean24(initTime=None,
fhour=24,
day_back=0,
model='中央气象台中短期指导',
map_ratio=19 / 9,
zoom_ratio=20,
cntr_pnt=[102, 34],
data_source='MICAPS',
south_China_sea=True,
area='全国',
city=False,
output_dir=None,
Global=False):
# prepare data
if (data_source == 'MICAPS'):
data_dir = [
utl.Cassandra_dir(data_type='surface',
data_source=model,
var_name='T2m')
]
fhours = np.arange(fhour - 21, fhour + 1, 3)
if (initTime is None):
initTime = utl.filename_day_back_model(day_back=day_back,
fhour=fhour)[0:8]
filenames = [initTime + '.' + str(fhour).zfill(3) for fhour in fhours]
T_2m = MICAPS_IO.get_model_grids(data_dir[0], filenames=filenames)
Tmean_2m = T_2m.isel(time=[-1]).copy()
Tmean_2m['data'].values[0, :, :] = np.mean(T_2m['data'].values, axis=0)
if (data_source == 'CIMISS'):
# get filename
fhours = np.arange(fhour - 18, fhour + 1, 3)
if (initTime is None):
initTime = utl.filename_day_back_model(day_back=day_back,
fhour=fhour,
UTC=True)[0:8]
T_2m = CMISS_IO.cimiss_model_by_times('20' + initTime,
valid_times=fhours,
data_code=utl.CMISS_data_code(
data_source=model,
var_name='TEF2'),
fcst_level=0,
fcst_ele='TEF2',
units='K',
allExists=False)
T_2m['data'].values = T_2m['data'].values - 273.15
Tmean_2m = T_2m.isel(time=[-1]).copy()
Tmean_2m['data'].values[0, :, :] = np.min(T_2m['data'].values, axis=0)
# set map extent
if (area != '全国'):
south_China_sea = False
if (area != None):
cntr_pnt, zoom_ratio = utl.get_map_area(area_name=area)
map_extent = [0, 0, 0, 0]
map_extent[0] = cntr_pnt[0] - zoom_ratio * 1 * map_ratio
map_extent[1] = cntr_pnt[0] + zoom_ratio * 1 * map_ratio
map_extent[2] = cntr_pnt[1] - zoom_ratio * 1
map_extent[3] = cntr_pnt[1] + zoom_ratio * 1
delt_x = (map_extent[1] - map_extent[0]) * 0.2
delt_y = (map_extent[3] - map_extent[2]) * 0.1
#+ to solve the problem of labels on all the contours
mask1 = (Tmean_2m['lon'] > map_extent[0] - delt_x) & (
Tmean_2m['lon'] < map_extent[1] + delt_x) & (
Tmean_2m['lat'] > map_extent[2] - delt_y) & (
Tmean_2m['lat'] < map_extent[3] + delt_y)
Tmean_2m = Tmean_2m.where(mask1, drop=True)
#- to solve the problem of labels on all the contours
Tmean_2m.attrs['model'] = model
Tmean_2m.attrs['title'] = '2米平均温度'
elements_graphics.draw_T_2m(T_2m=Tmean_2m,
T_type='T_mean',
map_extent=map_extent,
regrid_shape=20,
city=city,
south_China_sea=south_China_sea,
output_dir=output_dir,
Global=Global)